URSA-1.7B-IBQ512-UDMGRPO-PickScore Model Card
Method Details
Base Model Details
Examples
Using the 🤗's Diffusers library to run URSA in a simple and efficient manner.
pip install diffusers transformers accelerate imageio[ffmpeg]
pip install git+ssh://git@github.com/baaivision/URSA.git
Running the pipeline:
import torch
from diffnext.pipelines import URSAPipeline
model_id, height, width, guidance_scale = "Yovecents/URSA-1.7B-IBQ512-UDMGRPO-PickScore", 512, 512, 1.0
model_args = {"torch_dtype": torch.float16, "trust_remote_code": True}
pipe = URSAPipeline.from_pretrained(model_id, **model_args)
pipe = pipe.to(torch.device("cuda"))
prompt = "A cat on a propaganda poster wearing sunglasses"
image = pipe(**locals()).frames[0]
image.save("ursa.jpg")
Uses
Direct Use
The model is intended for research purposes only. Possible research areas and tasks include
- Research on generative models.
- Applications in educational or creative tools.
- Generation of artworks and use in design and other artistic processes.
- Probing and understanding the limitations and biases of generative models.
- Safe deployment of models which have the potential to generate harmful content.
Excluded uses are described below.
Out-of-Scope Use
The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.
Misuse and Malicious Use
Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
- Mis- and disinformation.
- Representations of egregious violence and gore.
- Impersonating individuals without their consent.
- Sexual content without consent of the people who might see it.
- Sharing of copyrighted or licensed material in violation of its terms of use.
- Intentionally promoting or propagating discriminatory content or harmful stereotypes.
- Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.
- Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.
Limitations and Bias
Limitations
- The autoencoding part of the model is lossy.
- The model cannot render complex legible text.
- The model does not achieve perfect photorealism.
- The fingers, .etc in general may not be generated properly.
- The model was trained on a subset of the web datasets LAION-5B and COYO-700M, which contains adult, violent and sexual content.
Bias
While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.